Machine Learning-Based Mechanism for Plant Health Management in Hydroponic Systems

Hydroponic is a technology for growing plant plants with soilless water, where plant growth is based on nutrient-rich solutions. IoT allows for practical monitoring and control of various environmental factors in hydroponic systems. The entire system can measure parameters such as temperature, air humidity, pH value, nutrient concentration, light intensity, and TD. Machine learning algorithms can optimize hydroponic systems. They analyze and make predictions for the relationships between plants and eco-friendly issues such as temperature, pH, nutritional levels, and humidity and TD. For better results, you will be recommended with mean predictions for handling and adjusting those factors to improve plant growth and yield. Machine learning can also forecast plant diseases and pest problems based on data about environmental factors and plant growth. Use of machine learning in hydroponics changes the sector because it supports much more precision and efficiency and even reduces crop costs, leading to increased yields. The present article shall manage resources better within hydroponic setups and requires low human intervention.